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1 How the Workplace Supports Successful Design 3 1.1 High-Speed Digital Design Is Challenging 3 1.2 Needs for Technical Specialization 6 1.3 The Role of Processes and Procedures 7 1.4 Using Judgment When Making Design Tradeoffs 8 1.5 HSDD Needs the Help of EDA Tools 9 1.6 HSDD Needs a Team That Extends Beyond the Company 9 1.7 HSDD Team Members Often Have Their Own Agendas 10 1.8 HSDD Simulations Performed in the Workplace 11 1.9 Modeling and Simulation Versus Prototype and Debug 12 1.10 Ten Tips for Modeling and Simulation 13 2 Introduction to Modeling Concepts 15 2.1 Modeling and Simulation for All Scales of System Size 15 2.2 Communicating Across Specialties 15 2.5 Needs for Model Accuracy Change as a Design Progresses.... 20 2.6 There Are Many Kinds of Models and Simulations 22 2.7 Modeling and Simulation for Systems 23 2.8 Bottom-Up and Top-Down Design 24 viii Semiconductor Modeling 2.9 Analog Issues in Digital Design 27 2.10 Noise Modeling on Electrical Signals 34 2.11 Additional Design Issues to Model and Simulate 36 2.12 Using EDA Tools for Semiconductors 41 2.13 Using EDA Tools for Board Interconnections 43 2.14 Looking Ahead in the Book 45 PART 2: GENERATING MODELS 47 3 Model Properties Derived from Device Physics Theory 49 3.2 Why Deep Sub-Micron Technology Is Complex 50 3.3 Models Extracted from Semiconductor Design Theory 52 3.4 Example of the BJT Process 53 3.5 How BJT and FET Construction Affect Their Operation 54 3.6 Calculating Device Physics Properties 65 3.7 Examples of Computing Electrical Properties from Structure. 71 3.8 Examples of SPICE Models and Parameters 75 3.9 Modeling Packaging Interconnections 90 4 Measuring Model Properties in the Laboratory 95 4.1 Introduction to Model Measurements 95 4.3 Scattering-Parameter Models 103 4.6 Web Sites for IBIS Visual Editors and Other Tools 126 4.7 TDR/TDT - VNA Measurements 126 4.9 Field Solver RLGC Extraction for ICs 130 4.10 What is Model Synthesis? 130 4.11 Test Equipment Providers 130 4.12 Software for Test Equipment Control 131 5 Using Statistical Data to Characterize Component Populations 133 5.1 Why Process Variation Is Important 133 5.2 Achieving Process Control with Population Statistics 133 5.3 Basics of Population Statistics 134 5.4 Characterization for Six-Sigma Quality 144 5.5 Six-Sigma Quality for Modeling and Design 149 Semiconductor Modeling ix PART 3: SELECTING COMPONENTS AND THEIR MODELS 151 6 Using Selection Guides to Compare and Contrast Components 153 6.1 Tools for Making Component Choices 153 6.2 Team Members Use of Selection Guides 155 6.3 Selection Guide Examples 156 6.4 Selection Guides Help Component Standardization 161 6.5 Simulation as a Selection Guide 161 7 Using Data Sheets to Compare and Contrast Components 169 7.1 Data Sheets as Product Descriptions 169 7.2 Are Data Sheets Accurate and Complete? 173 7.3 Selecting a Component That Is Fit for Use 175 7.4 Using Data Sheets to Begin the Selection Process 176 7.5 Construction Characteristics of Amplifiers and Switches 178 7.6 Using Beta to Explain Device Tradeoffs 179 7.7 Comparing Five BJTs to Illustrate Making a Selection 182 7.8 Process for Making Tradeoffs 195 7.9 Additional Choices for Picking a Component 197 7.10 Thoughts About the Physical Design Examples 197 8 Selecting the Best Model for a Simulation 199 8.1 From Component Choice to Model Choice 199 8.2 Questions That Modeling and Simulation Can Answer 200 8.4 Using Symbols and Schematics to Represent Models 202 8.5 Major Types of Models 205 8.6 Compare Models by Simulation Performance 211 8.7 Additional Model Comparisons 221 8.8 Recommendations for Modeling 223 8.9 Converting a Model to Another Type of Model 227 8.10 Transform Models for Systems 234 9 Modeling and Simulation in the Design Process Flow 243 9.1 Simulation in the Design Process 243 9.2 A Typical Design Flow 244 9.3 Strategy of Modeling and Simulation in Design 248 9.4 Acquiring IBIS Models: An Overview 249 PART 4: ABOUT THE IBIS MODEL 259 10 Key Concepts of the IBIS Specification 261 10.2 IBIS Specification 264 10.3 Sample IBIS Data File 283 10.4 Parsing and Checking IBIS Data Files 294 10.5 Schematic of a Basic IBIS Model 297 10.6 How IBIS Circuit Modeling Methodology Is Used 301 10.7 IBIS Test Circuits 309 10.8 ISO 9000 Process Documentation for IBIS Models 310 11 Using IBIS Models in What-If Simulations 315 11.1 A New Method of Design and Development 315 11.2 Virtual Experiments 316 11.3 Virtual Experiment Techniques 316 11.4 Propagation Delay in High-Speed Nets 317 11.5 Why We Use the IBIS Model 318 11.6 Data Used in Experiments 320 11.7 Experiment 1: Output Drive Capabity Versus Load 322 11.8 Experiment 2: Ccomp Loading 327 11.9 All-Important Zo: Algorithms and Field Solvers 332 11.10 Experiment 3: Edge Rate of a Driver and Reflections 333 11.11 Experiment 4: Using V-T Data Versus a Ramp 336 11.12 Experiment 5: Parasitics and Packaging Effects 346 11.13 Experiment 6: Environmental and Population Variables 349 11.14 Other Considerations: Timing and Noise Margin Issues 352 11.15 Experiment 7: Vol from Simulation Versus Data Sheet 356 11.16 How IBIS Handles Simulator Issues 358 12 Fixing Errors and Omissions in IBIS Models 361 12.1 IBIS Model Validation Steps 361 12.2 Process and Product Improvement Steps 362 12.3 Step 1: Detect and Acknowledge the Quality Problem 363 12.4 Step 2: Diagnose the Problem's Root Cause 364 12.5 Step 3: Design a Fix Based on Root Cause 366 12.6 Step 4: Verify the Fix 370 12.7 Step 5: Archive Corrected Models 372 12.8 Beyond Parsers and Checklists: Simulations and 12.9 Tools Provided by the IBIS Committee 374 12.10 IBIS Common Errors Checklist and Correction Procedures.. 382 12.11 3Com's ISO 9000 Process for IBIS Models 386 Semiconductor Modeling xi 12.12 IBIS Model Acceptance and Legitimacy 391 13 Using EDA Tools to Create and Validate IBIS Models from 13.2 I/O Buffer Example 396 13.3 SPICE-to-IBIS Conversion Methodology 399 13.4 Modeling Passive Interconnections in IBIS 414 13.5 IBIS Model Validation 415 PART 5: MANAGING MODELS 425 14 Sources of IBIS Models 427 14.1 Model Needs Change as a Product is Developed 427 14.2 List of IBIS Model Sources 428 14.3 Using Default Models to Get Started 430 14.4 Using the Company's Model Library 430 14.5 Using the EDA Tool Provider's Model Library 430 14.6 Searching the Web for the SuppHer's Model 431 14.7 Requesting Models Directly from the Supplier 434 14.8 Purchasing a Commercial Third-Party Model Library 436 14.9 Using Models Adapted from Other Models 437 14.11 Purchasing Custom Models from a Third-Party 441 14.12 Converting SPICE Models to IBIS Models 441 14.13 Using a Supplier's Preliminary Models 441 14.14 Asking SI-List and IBIS E-mail Reflectors for Help 450 14.15 Modeling Tools on the IBIS Website 451 15 Working with the Model Library 453 15.1 The Best Way to Manage Models 453 15.2 Component Standardization and Library Management 458 15.3 Storing and Retrieving Model Files 470 15.4 Assigning Models to Components in EDA Simulators 473 15.5 Flexibility in Model Choices at Run Time 476 PART 6: MODEL ACCURACY AND VERIFICATION 477 16 Methodology for Verifying Models 479 16.1 Overview of Model Verification 479 16.2 Model Verification Methodology 481 xii Semiconductor Modeling 16.3 Verifying SPICE Models 489 16.4 Verifying PDS Models 497 16.5 Verifying IBIS Models 503 16.6 Verifying Other Model Types 508 17 Verifying Model Accuracy by Using Laboratory Measurements .... 511 17.2 Instrumentation Loading as a Source of Errors 512 17.3 Other Test Setup Errors 517 17.4 Signal Noise as a Source of Errors 519 17.5 Measurement Definitions and Terms as a Source of Errors... 520 17.6 Two Ways to Correlate Models with Measurements 522 17.7 Involving Production in Verification 523 17.8 An EMI/EMC Example 523 17.9 Correlating Unit-by-Unit Model Measurements 524 17.10 Statistical Envelope Correlation 525 17.11 Signal Integrity and Correlation 526 17.12 Waveform Correlation 527 17.13 Computational Electromagnetics and the Feature Selective Validation Method 530 17.14 IBIS Golden Waveforms 534 17.15 How Unexpected Errors Led to an Advance in Modeling 535 17.16 Recommended Verification Strategy 541 18 Balancing Accuracy Against Practicality When Correlating 18.1 Establishing Absolute Accuracy Is Difficult 545 18.2 Is a Model Accurate Enough to Be Usable? 547 18.3 Model Accuracy Definitions 547 18.4 Confidence Limits in Measurements and Simulations 548 18.5 How Much to Guard-Band Design Simulation? 549 18.6 Differences in Accuracy, Dispersion, and Precision for Simulation and Measurement 550 18.7 Model Limitations 551 18.8 Standardization and the Compact Model Council 551 19 Deriving an Equation-Based Model from a Macromodel 555 19.1 A "New" RF Design Challenge 555 19.3 Applying the RF Example to High-Speed Digital Circuits.... 556 19.4 Predicted and Measured Results 558 19.5 Reverse Isolation Analyzed 559 Semiconductor Modeling xiii 19.6 Optimizing Single-Stage Reverse Isolation 566 19.7 Combining Stages for Power Isolation 567 19.8 Calculations Versus Measurements 569 19.9 Construction and Test Techniques 569 PART 7: FUTURE DIRECTIONS IN MODELING 571 20 The Challenge to IBIS 573 20.1 Emerging Simulation Requirements 573 20.2 The Leading Contenders to Change IBIS 576 20.3 Models in the Context of Simplification 577 20.4 Physical Modeling 578 20.5 Behavioral Modeling 580 20.6 Developing a Macromodel from the Behavioral Model 588 20.7 Developing a SPICE Macromodel from a Physical Model.... 592 20.8 Limitations in Models Due to Simplification 608 20.9 AMS Modeling Simplified 610 20.10 Limitations Because of Parameter Variation 618 20.11 Limitations of Deterministic Modeling and Design 621 21 Feedback to the Model Provider Improves Model Accuracy 631 21.1 Continuing Need for Better Models 631 21.2 How Far We Have Come 632 21.3 Four-Step Universal Process for Improvement 633 21.4 Specs That Swim Upstream; A New Approach 633 21.5 Warnings About Doing What-If Model Simulations 634 21.6 Selling the Idea of Better Models and Simulation 635 22 Future Trends in Modeling 641 22.1 Bridges to the Future 641 22.2 Challenge of HSDD 642 22.3 How Design Methods Have Changed 644 22.4 Attitudes in EMI/EMC about Modeling and Simulation 645 22.5 High-Speed Design Is Becoming More Challenging 646 22.6 Advantages of SPICE, S-Parameters, and IBIS 648 22.7 Combining Models and EDA Tools to Design High-Speed Serial Busses 654 22.8 IBIS: Past, Present, and Future Specification Additions 655 22.9 Advantages of Pre-Layout Simulation for EMI/EMC 659 22.10 Interconnection Design Applied to EMI/EMC 660 22.11 Modeling for Power Integrity and EMI/EMC 661 xiv Semiconductor Modeling 22.12 Computational Electromagnetics 671 22.13 EDA Tool Supplier Survey 676 22.14 Risk Management and the Limitations of Simulation 681 23 Using Probability: The Ultimate Future of Simulation Contributing author: Darren J. Carpenter, BTExact 683 23.2 Limitations of Deterministic Modeling and Design 685 23.3 A New Approach: Probabilistic Modeling 687 23.4 Complexity of the EMI Chain of Cause and Effect 688 23.5 Risk Management Mathematics 689 23.6 Identical Equipments Case 692 23.7 Non-Identical Equipments Case 693 23.9 Distribution Examples 694 23.10 Review of Probability Distributions 701 23.11 Follow Up Simulation with Product Assurance 702 PART 8: GLOSSARY, BIBLIOGRAPHY, INDEX, AND CD-ROM 705 Using the Companion CD-ROM | 
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